Yes, that's what I was looking for. Thanks. On Tue, Apr 12, 2016 at 9:28 AM, Nick Pentreath <nick.pentre...@gmail.com> wrote:
> Are you referring to fitting the intercept term? You can use > lr.setFitIntercept (though it is true by default): > > scala> lr.explainParam(lr.fitIntercept) > res27: String = fitIntercept: whether to fit an intercept term (default: > true) > > On Mon, 11 Apr 2016 at 21:59 Daniel Siegmann <daniel.siegm...@teamaol.com> > wrote: > >> I'm trying to understand how I can add a bias when training in Spark. I >> have only a vague familiarity with this subject, so I hope this question >> will be clear enough. >> >> Using liblinear a bias can be set - if it's >= 0, there will be an >> additional weight appended in the model, and predicting with that model >> will automatically append a feature for the bias. >> >> Is there anything similar in Spark, such as for logistic regression? The >> closest thing I can find is MLUtils.appendBias, but this seems to >> require manual work on both the training and scoring side. I was hoping for >> something that would just be part of the model. >> >> >> ~Daniel Siegmann >> >
